IFPRI Discussion Paper 01690

December 2017

Agro-processing and Horticultural Exports from Africa

Emiko Fukase

Will Martin

Markets, Trade, and Institutions Division

INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE

The International Food Policy Research Institute (IFPRI), established in 1975, provides evidence-based

policy solutions to sustainably end hunger and malnutrition and reduce poverty. The Institute conducts

research, communicates results, optimizes partnerships, and builds capacity to ensure sustainable food

production, promote healthy food systems, improve markets and trade, transform agriculture, build

resilience, and strengthen institutions and governance. Gender is considered in all of the Institute’s work.

IFPRI collaborates with partners around the world, including development implementers, public

institutions, the private sector, and farmers’ organizations, to ensure that local, national, regional, and

global food policies are based on evidence.

AUTHORS

Emiko Fukase (emikof2@aol.com, efukase@worldbank.org) is an economist in the Development

Research Group at the World Bank, Washington, DC.

Will Martin (w.martin@cgiar.org) is a Senior Research Fellow in the Markets, Trade, and Institutions

Division of the International Food Policy Research Institute, Washington, DC.

Notices

1 IFPRI Discussion Papers contain preliminary material and research results and are circulated in order to stimulate discussion and

critical comment. They have not been subject to a formal external review via IFPRI’s Publications Review Committee. Any opinions

stated herein are those of the author(s) and are not necessarily representative of or endorsed by the International Food Policy

Research Institute.

2 The boundaries and names shown and the designations used on the map(s) herein do not imply official endorsement or

acceptance by the International Food Policy Research Institute (IFPRI) or its partners and contributors.

3 Copyright remains with the authors.

iii

Contents

Abstract v

Acknowledgments vi

1. Introduction 1

2. Changing Patterns of Processing and Exports 3

3. Global Perspective on Agricultural Processing and Horticultural Exports 8

4. Trade and Protection Patterns 20

5. Simulation Scenarios and Results: Trade Effects 26

6. Policy Questions 31

7. Conclusions 38

Appendix 40

References 49

iv

Tables

Table 3.1 Revealed comparative advantage of African exports 9

Table 3.2 Export shares for six-digit agricultural goods, 2013 13

Table 3.3 Composition of SSA’s top 20 exports to the world and to SSA, 2013 16

Table 4.1 Structure of ad valorem equivalent protection 22

Table 5.1 Simulation results: trade effects (%) 27

Table 6.1 Output per worker and the cost of labor in special economic zones and

economy-wide GDP per capita 36

Table A.1 Composition of top 20 agricultural exports at the country level, 2013 ($1,000) 40

Table A.2 List of bottom 2 percent items that made top 20 list in 2013 45

Figures

Figure 3.1 Export shares from Sub-Saharan Africa 8

Figure 3.2 Shares of agricultural exports 11

Figure 3.3 The share of processed agricultural value added in total agricultural

value added rises with per capita income, 2011 18

Figure 3.4 The share of processed agricultural exports in total agricultural exports also

rises with per capita income, 2011 19

Figure 4.1 Destinations of SSA’s exports, 2011 21

Figure 4.2 Intra-SSA direction of trade for agricultural goods, 2011 ($ million) 25

v

ABSTRACT

Sub-Saharan African exports of horticultural and processed agricultural products are growing in line with

the major shift toward these products in world markets. Continued growth in such exports may be vitally

important for expanding returns from African agriculture and for increasing Africa’s overall exports.

Policy reforms such as reductions in the tariff escalation facing Africa, improvements in the productivity

of agricultural processing, and reductions in trade barriers within Africa and beyond would all further

stimulate exports of processed agriculture. While essential, expansion of these exports should be regarded

as complementary to—rather than a substitute for—development of other dynamic export sectors.

Keywords: Africa, agro-processing, trade, horticulture

JEL classification: F13, F17, F63, Q17

vi

ACKNOWLEDGMENTS

This paper is reproduced by permission of the United Nations University World Institute for Development

Economics Research (UNU-WIDER), Helsinki, which commissioned the original research and holds

copyright thereon. The authors would like to thank Richard Newfarmer, John Page, and Finn Tarp for

guidance and suggestions; and Antoine Bouët, David Laborde, Jonathan Nelson, Rob Vos and

participants in an authors’ workshop in Helsinki for valuable comments. We are grateful to UNU-WIDER for funding support, and to the CGIAR Research Program on Policies, Institutions, and Markets, led by the International Food Policy Research Institute, and the World Bank Strategic Research Program for partial financial support.

1

1. INTRODUCTION

Agricultural exports from Sub-Saharan Africa (SSA)1 include a much larger share of bulk agricultural

exports than is the norm on world markets, where processed products have come to dominate. In looking

at how Africa might move beyond traditional bulk exports and the resource-based exports that are also

disproportionately important in Africa, a few questions appear to be key. Should African exports move

into labor-intensive manufactures of the type that have dominated the export-led growth of Asian

economies from Hong Kong, Korea, and Taiwan (China), through China, Bangladesh, Cambodia, and

Vietnam (Page 2012; Newman et al. 2016b)? Should they pursue alternative approaches such as adding

value to existing agricultural exports or developing new high-value agricultural exports? Or should policy

makers undertake strategies to encourage entrepreneurs to look everywhere for opportunities, recognizing

that it will often be difficult to find successes, but that the rewards from identifying a highly successful

export are very great (Hausmann and Rodrik 2003; Easterly and Reshef 2010)?

While it is well known that the share of the agricultural sector in an economy typically declines

with economic growth, it is less known that the share of the agro-processing sectors in gross domestic

product (GDP) tends to increase as local consumption shifts from raw, starchy staple foods to foods such

as vegetables, fruits, and meats and as food consumed comes to embody more services (da Silva et al.

2009). We examine whether SSA is following this pattern and whether agricultural exports from Africa

are moving from bulk products to processed and horticultural goods. Given SSA’s current income, is this

an area in which Africa is lagging and potentially large gains can be made? Or are African exporters

already acting to exploit potential gains?

Export growth is vitally important for a wide range of reasons, as it promotes economic growth,

creates jobs (Calì and Hollweg 2017; Fukase 2013), and is a source of the foreign exchange needed to

import goods that cannot readily be produced locally. Domestic and international policies, however,

influence both the level and the mix of products that are traded. In recent years, the “trade in tasks” in the

1 The focus of this paper is SSA countries. Throughout the paper, we use the terms “SSA” and “Africa” interchangeably.

2

new wave of globalization (Baldwin 2006, 2016) appears to have been creating new opportunities for African

countries to tap into export markets, as they enjoy a number of location-specific comparative advantages.

How should African governments act to influence the development of nontraditional exports, such as

those from agro-processing operations, or high-value export crops such as horticultural products, or both?

This paper analyzes the principal features of agro-processing and horticultural exports from SSA

and explores policy alternatives based on simulation analyses. We first provide a conceptual section

focusing on changing patterns of processing and exports (section 2). We then examine how the pattern of

exports from Africa compares with the pattern in other regions (section 3). Following that, we examine

the directions of trade in African agricultural exports and the patterns of protection facing, and imposed

by, African countries (section 4). Next, we turn to simulation exercises to examine the impacts of

potential reforms on exports of processed and horticultural exports from Africa (section 5). With this as

background, we turn to consider the options for policy makers in Africa (section 6). The final section

presents a brief conclusion (section 7).

3

2. CHANGING PATTERNS OF PROCESSING AND EXPORTS

Prior to the Industrial Revolution and the development of steam transport, international trade was very

limited because of high transport and communication costs. Some very high value-to-weight items such

as spices and gemstones were traded over long distances, but most foods and manufactures were produced

locally. Basic production patterns and income levels were very similar across the world.

As noted by Baldwin (2006, 2016), the first wave of globalization frequently involved the

production of raw materials in developing countries, with the processing of those products into final

manufactured goods generally taking place through vertically integrated production processes in

industrial countries. During this phase of industrialization, communications were not sufficiently well

developed to allow coordination of activities at a distance, and the capital needed for industrial

development tended to be most readily available in the industrial countries. This pattern of

industrialization appeared to generate many gains from learning-by-doing in the industrial countries and

to contribute to a major divergence in income levels, with incomes in the industrial countries rising far

above the levels in developing countries.

Developing countries, understandably, were unhappy with this model of industrial development

and frequently tried to develop their own integrated industrial sectors, often by creating incentives to

process the raw materials that they produced, as suggested by Alexander Hamilton in his “Report on

Manufactures” published in 1791 (McKee 1934). Unfortunately, this typically proved to be very difficult

to achieve without excessive cost and loss to the producers of raw materials. Even where plans and

prototypes of processing plants from other countries were available, it frequently proved difficult to

operate them successfully (Hausmann and Rodrik 2003).

During this first phase of globalization, the initial processing stages needed to preserve, or to

lower, the weight of raw material exports were established in producing areas. Activities of this type

include cotton ginning, processing coffee cherries into dry coffee beans, initial processing of tea, and

slaughter of livestock. Some export-oriented processing activities going beyond this stage were

4

undertaken in developing countries, such as the transformation of cotton into textiles in India and

Pakistan, but they were the exception rather than the rule. Sometimes, these activities were artificially

induced by imposing taxes or quantitative restrictions on exports of raw materials—frequently under the

banner of “value adding.” A key problem with this approach is that—unless the activity can be performed

efficiently in the country—the associated high processing costs reduce the amount available for payment

to the producers of the raw material. This is both inefficient and inequitable when the suppliers of the raw

material are small, low-income producers. Unfortunately, this problem was quite common when countries

sought to increase the processing of their commodities—whether for export or, more commonly, for

domestic consumption—because many processing activities were capital and skill intensive and difficult

to undertake economically in countries very poorly endowed with capital and skilled workers.

In recent years, changes in the costs and allocation of factors have created new opportunities for

developing countries in both industrial production and further processing of agricultural commodities.

Lower transport and communication costs have made it possible for more parts of the production process

to be conducted in different locations, depending upon the competitiveness of the particular activity in

that location. Production of garments, for example, may involve growing cotton in West Africa where

agro-ecological conditions are particularly suited; making yarn and fabric (likely using blends of cotton

and other fibers) in China; assembling garments in Bangladesh; and enabling the transfer of information,

such as the designs for clothes and the authorization of production samples, to take place over great

distances. To exploit cost advantages created by these developments, firms from more advanced countries

are increasingly willing to bring the capital and knowledge needed for successful production via foreign

direct investment. This can obviate the very long process of learning otherwise needed to establish an

entirely new export activity (Hausmann and Rodrik 2003).

This new approach to production has opened up opportunities for developing countries not

available under the earlier approach to industrialization. Countries such as China, Vietnam, and

Bangladesh have developed export-oriented manufacturing systems that are deeply engaged in this

production system. Thailand has been very active in agro-processing, frequently using domestically

5

produced products but sometimes using imported inputs. This new form of industrialization has been

associated with a dramatic change in the distribution of world income, with countries that have engaged

in this process raising their average incomes and lowering poverty rapidly. Unhappiness about this

approach to development appears to be emerging in high-income countries, based on perceptions about

loss of manufacturing jobs to developing countries, although the evidence suggests that automation has

been a more important contributor to that phenomenon, and the decline in the share of manufacturing is a

global phenomenon.

The unbundled approach to global value chains involves much greater transfer of materials than

the traditional approach and hence is more demanding of logistics than traditional approaches. Issues such

as low transport costs and smooth customs clearance become important for the organization of

production. Once efficient logistics are in place, however, countries with suitable agro-ecological

conditions can potentially produce high-value products, such as cut flowers and fresh vegetables, which

formerly needed to be produced near their point of consumption. In this case, the logistics and trade

facilitation are also vitally important, given the high costs of delay. African producers of products such as

green beans, cut flowers, and fresh fruit appear to have seized some of these opportunities.

A recent improvement in economists’ approaches in the analysis of exports involves a recognition

of the diversity of experience by firms and with particular products. While trade theory did not explicitly

consider firms until the 1990s, the availability of transaction-level data revealed striking heterogeneity of

firms, with most exports accounted for by a surprisingly small share of firms. Further, these firms tended

to be more productive than nonexporting firms even when they began exporting—in contrast with the

traditional model in which firms learned by doing in the very different business environment facing

exporting firms. Only the most productive firms also tended to export multiple products and to multiple

export markets. While these findings were originally established for industrial countries (for example,

Bernard and Jensen 1995), they were quickly confirmed for developing countries (Clerides, Lach, and

Tybout 1998) and subsequently for exports of processed agricultural products (Gopinath, Sheldon, and

Echeverria 2007).

6

In Africa, considerable evidence has emerged that exporting firms are—as in other regions—

more productive and pay higher wages than nonexporting firms (Bigsten et al. 2004; Van Biesebroeck

2005; Brambilla, Chauvin, and Porto 2015). However, there are also indications that firms continue to

benefit from learning-by-doing after entering export markets (Bigsten et al. 2004; Mengistae and Pattillo

2004; Van Biesebroeck 2005; Newman et al. 2016a). Using firm-level panel data from three SSA

countries, Mengistae and Pattillo, in particular, find that the productivity of exporting firms grows

10 percent faster than that of nonexporting firms. A recent paper studying the case of Ghana by Mulangu

and Olarinde (2016) finds evidence of learning-by-doing, but no evidence of higher-productivity firms

selecting into exporting. It also concludes that the fixed costs associated with starting exports to African

countries are lower than those to other markets—suggesting that intra-African exports may provide an

opportunity for more firms to export, and to reap the productivity gains associated with exporting.

Another recent perspective on developing-country exports has come from the realization that

exports from most countries are dominated by a relatively small range of specific products (Hausmann

and Rodrik 2003). This is the case for even very large countries such as China and India for which only

one six-digit product (unrefined petroleum) appears on the list of top-25 exports in both countries

(Dimaranan, Ianchovichina, and Martin 2007). Easterly and Reshef (2010) find that exports from several

African countries are dominated by a small number of “big hits” with large export shares.

Whether African exports are highly specialized or not has important implications for the volatility

of export returns because highly concentrated export bundles are much more likely to be volatile than

more diversified export bundles. Adding processed agricultural exports to an export bundle dominated by

something else—such as resource exports—may reduce volatility. However, switching from exporting a

raw product to exporting the same product in processed form might not lead to a substantial reduction in

export volatility, if the price received for the processed product is heavily influenced by the price of the

raw material. Diversifying from agricultural and resource products to manufactures seems likely to

provide the largest gains from diversification.

7

Another factor influencing export outcomes is whether markets for particular products are

expanding or contracting. When markets are growing, prices are more likely to be buoyant in order to

provide an incentive for additional resources to flow into the sector. In shrinking markets, competition

between suppliers—and particularly suppliers with large fixed investments in production—is more likely

to put downward pressure on prices. With income growth, consumers are likely to move from purchasing

raw agricultural products to consuming products with additional embedded services (da Silva et al. 2009).

For this reason, it seems more likely that markets for processed agricultural products will grow more

rapidly than markets for raw products when incomes rise in consuming countries. Demand for horticultural

products such as tropical fruits and fresh flowers is also likely to grow relatively rapidly as incomes rise,

potentially making the exports of these products grow faster than staple agricultural products.

8

3. GLOBAL PERSPECTIVE ON AGRICULTURAL PROCESSING AND HORTICULTURAL EXPORTS

In this section, we first examine the evolution of exports from SSA and other regions. Figure 3.1 shows

the composition of Africa’s exports of goods and services, divided into agriculture, resources,

manufactures, and services. Figure 3.1 reveals the small share of agriculture in African exports at around

10 percent, which is lower than the 12 percent accounted for by exports of nonfactor services. This low

share of agriculture in total exports suggests that the opportunities for expanding total exports by

processing existing agricultural exports—some of which are already processed—are likely to be more

limited than where exports of unprocessed agricultural products account for a large proportion of total

exports.

Figure 3.1 Export shares from Sub-Saharan Africa

Source: Merchandise export data from Comtrade, accessed through World Integrated Trade Solution (World Bank 2016a).

Exports of services from World Development Indicators (World Bank 2016b).

Because the relative share of different export categories depends partly on factors such as the prices of

agricultural and resource commodities, and on the importance of each good in world trade, we compare

0%

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the export structure of SSA with global export patterns using an index of revealed comparative advantage

(RCA) (Balassa 1965). This index compares shares of exports from SSA with the corresponding global

shares. Table 3.1 indicates that the RCA of Africa in agriculture has fallen from 2 to 1.5 since 1992. The

RCA for resources exports has also declined—from 4.5 to 3.2, while that for manufactures has risen

slightly, from 0.4 to 0.5. These results suggest that African exports have moved somewhat closer to the

world average over the past two decades.

Table 3.1 Revealed comparative advantage of African exports

SSA countries SSA without oil exporters

Year Agriculture Resources Manuf. Services Agriculture Resources Manuf. Services

1992 2.0 4.5 0.4 0.7 2.7 2.5 0.5 0.8

1995 2.5 4.2 0.4 0.8 3.2 2.3 0.5 0.8

2000 2.3 4.2 0.4 0.7 3.2 2.0 0.6 0.8

2005 1.9 3.6 0.4 0.7 2.9 1.6 0.7 0.8

2010 1.6 3.5 0.4 0.6 2.6 1.8 0.7 0.8

2014 1.5 3.2 0.5 0.6 2.3 1.5 0.8 0.7

Source: Merchandise export data from Comtrade, accessed through World Integrated Trade Solution (World Bank 2016a).

Exports of services from World Development Indicators (World Bank 2016b). The RCA for good j from region i is defined as

Xij/Xi/Xwj/Xw where Xi is total exports from region i and index w refers to world exports.

Notes: Countries are classified as oil exporters if the share of fuel exports relative to gross domestic product is above 10 percent.

SSA = Sub-Saharan Africa.

For non-oil exporting African countries, we see a similar pattern of decline in the RCA for

agricultural and resource products, although the agricultural product RCA is substantially above that for

the region as a whole. The increase in the RCA for exports of manufactures is much stronger for the non–

oil exporters, rising from 0.5 to 0.8.

Between 1988 and 2014, world agricultural exports grew from $83.4 billion2 to $1,532 billion

while SSA’s agricultural exports increased from $2.7 billion to $44.3 billion (the UN Comtrade

System). As a result, SSA’s share in world agricultural exports declined from 3.3 percent in 1988 to

2.9 percent in 2014. We distinguish among agricultural products using the Regmi et al. (2005)

definitions of bulk, semiprocessed, and processed agricultural products, plus horticultural products. As

2 All figures are in US dollars. In 1988, agricultural exports were 9.6 percent of world exports of goods and services, and

declined to 7.2 percent in 2014.

10

noted by Liapis (2011, 12), bulk and horticultural products are tied strongly to geographic conditions,

while semiprocessed products such as sugar or cocoa products and processed products such as meat and

chocolate are less geographically linked and could potentially be produced using inputs from other

locations. With these definitions, we see a sharp difference between Africa and the world as a whole.

As shown in Figure 3.2, for the world as a whole, bulk agricultural products account for a small and

declining share of agricultural exports—decreasing from 25 percent in 1988 to 17 percent in 2014. By

contrast, processed and semiprocessed agricultural products accounted for almost three-quarters of

global agricultural exports by 2015. Horticultural exports accounted for around 12 percent of global

agricultural exports in 2014.

For Africa, the corresponding patterns are quite different. The share of bulk agricultural exports

also declined, but from around 60 percent to 42 percent in 2014, leaving these exports still as a large

share of total agricultural exports. The share of processed and semiprocessed agricultural products rose,

but only to 35 percent by 2015. If African countries are relatively abundant in raw agricultural goods

and scarce in capital, a larger share of bulk exports relative to processed agricultural products is consistent

with the Heckscher-Ohlin-Samuelson model, which predicts that countries export products that use

relatively abundant factors of production. The share of horticultural exports rose from around 10 percent

in 1988–1989 to 22 percent in 2014. It seems clear that African exporters are adjusting to the changes

in the world markets, but doing it in a distinctively African way. In particular, the expansion of

horticultural exports suggests that Africa has seized new opportunities, for instance, in becoming

integrated into global agricultural value chains in flowers and horticultural crops (Minten, Randrianarison,

and Swinnen 2009).

11

Figure 3.2 Shares of agricultural exports

Source: Merchandise export data from Comtrade, accessed through World Integrated Trade Solution

(World Bank 2016a).

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Bulk Proc Semi Proc Hort

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12

To look in more detail at agricultural exports from Africa, we consider individual six-digit

products using the Harmonized System product definitions—the finest for which internationally

comparable measures are available. In Table 3.2, we examine these products for 10 focus countries and

for SSA as a whole. The table shows the export value share for each of the top 20 agricultural exports, the

share held by the top 20 products, the number of agricultural exports, and the numbers equivalent of the

Herfindahl index for agricultural exports (Adelman 1969). This numbers-equivalent measure—measured

as 1

∑𝑆𝑖2 where Si is the share of each product in the total—shows the number of equally distributed exports

that would provide the same degree of diversification as the observed set of exports, assuming

independent and identically distributed volatility for each commodity export.

13

Table 3.2 Export shares for six-digit agricultural goods, 2013

Rank Ethiopia Ghana Kenya

Mozam-

bique Nigeria Rwanda Senegal S. Africa Tanzania Uganda

SSA as a

group SSA to SSA

1 23.3 59.0 39.6 37.1 32.1 22.1 13.9 7.3 12.2 30.4 12.8 7.9

2 16.9 9.9 15.7 27.6 17.6 18.6 12.6 6.2 11.9 6.8 4.7 4.2

3 15.9 7.9 6.2 4.7 5.6 8.7 6.4 5.3 9.2 6.0 4.7 3.9

4 15.0 4.5 3.2 4.5 5.0 7.9 5.7 4.6 6.8 4.9 4.4 3.2

5 6.5 2.8 2.9 3.3 4.0 5.9 5.5 4.6 5.2 4.2 3.8 2.9

6 4.5 1.4 2.3 2.4 3.5 4.2 4.5 3.4 4.2 3.9 2.7 2.8

7 2.2 1.4 2.0 2.0 3.4 3.2 4.2 2.2 4.0 3.4 2.7 2.6

8 1.9 1.0 1.7 1.6 3.2 3.2 4.2 2.2 3.5 2.9 2.2 2.4

9 1.9 0.9 1.4 1.3 2.6 3.1 4.2 2.0 3.2 2.2 2.1 2.3

10 1.4 0.8 1.2 1.1 2.4 2.9 3.0 2.0 2.9 2.1 1.7 1.9

11 1.2 0.8 1.2 1.1 2.0 2.9 2.9 1.9 2.9 2.1 1.7 1.8

12 0.9 0.7 1.2 0.9 1.5 2.3 2.4 1.7 2.0 2.0 1.6 1.8

13 0.9 0.7 1.1 0.9 1.2 1.8 1.9 1.4 1.9 1.8 1.6 1.7

14 0.7 0.6 1.0 0.8 1.1 1.4 1.9 1.3 1.9 1.7 1.5 1.4

15 0.7 0.6 0.9 0.8 1.1 1.0 1.7 1.3 1.7 1.6 1.5 1.3

16 0.6 0.6 0.9 0.7 1.0 1.0 1.6 1.1 1.7 1.4 1.5 1.2

17 0.4 0.5 0.8 0.7 0.9 0.9 1.6 1.1 1.2 1.3 1.3 1.1

18 0.4 0.5 0.7 0.7 0.9 0.7 1.5 1.0 1.2 1.3 1.2 1.1

19 0.3 0.5 0.7 0.6 0.6 0.6 1.4 1.0 1.1 1.2 1.1 1.0

20 0.3 0.3 0.6 0.6 0.5 0.6 1.1 1.0 1.1 1.1 1.1 1.0

Top 20

share 96.2 95.5 85.4 93.5 90.2 93.0 82.2 52.7 79.8 82.4 55.9 47.8

No. of

exports 249 362 520 208 299 233 591 655 357 402 670 662

Nos.

equiv. 7 3 5 5 7 9 17 44 18 9 33 54

Source: Merchandise export data from Comtrade, accessed through World Integrated Trade Solution (World Bank 2016a).

Note: SSA = Sub-Saharan Africa.

14

Table 3.2 shows that agricultural exports from African countries tend to be highly concentrated,

with the largest export having a very large share of total agricultural exports, and subsequent exports

having much smaller shares.3 Consistent with this, the top 20 exports accounted for 80 percent or more of

export returns in each of our focus countries except South Africa, and more than 90 percent in five of our

focus countries. While each country has what appears to be a large number of agricultural exports

(between 208 and 655), the very large shares accounted for by the top products mean that these export

baskets are much less diversified than they might at first appear. The numbers equivalent of the

Herfindahl index suggests that, for instance, the 362 agricultural exports from Ghana provide the export

market diversification that would be provided by having just three equally distributed agricultural exports.

The 520 and 208 agricultural exports from Kenya and Mozambique, respectively, provide little more

diversification, being equivalent to only five identically distributed products. In contrast, the agricultural

export baskets of Senegal, Tanzania, and South Africa are much more diversified, being equivalent to 17,

18, and 44 products, respectively—numbers which should provide considerable diversification. The lack

of diversification in African exports is consistent with the findings of other studies. For instance,

calculating the global geographic diversification index (De Lombaerde and Lapadre 2012) and the global

sectoral diversification index, Bouët, Cosnard, and Laborde (2017) find low levels of product and partner

diversification for African exports.

The last two columns of Table 3.2 show the results for SSA as a group for agricultural goods that

went to the world and to SSA, respectively. The exports that went to SSA turn out to be somewhat more

diversified: SSA’s top 20 exports to the world and to the SSA accounted for 56 percent and 48 percent,

respectively, while the corresponding indexes were 33 and 54. This may reflect the relatively low entry

costs into exporting to SSA countries reported by Mulangu and Olarinde (2016). It may also reflect a

tendency to re-export high-value processed agricultural items—often imported from outside Africa.

3 Following Easterly and Reshef (2010), we plotted the log of the rank for each export against the log of its export share and

confirmed that these distributions followed a power law, under which a small share of products accounts for a very large share of

exports.

15

Table 3.3 shows the composition of the top 20 exports for SSA as a group to the world and to

SSA. Table 3.3 also categorizes SSA’s exports into bulk (B), horticulture (H), and processed (P) agriculture,

which are shaded in blue, green, and pink, respectively. In terms of SSA’s exports to the world (first

panel), the five top items are dominated by bulk exports—cocoa beans, coffee, unmanufactured tobacco,

sesamum seeds, and black tea. Fresh cut flowers and horticulture products such as cashew nuts and fresh

fruit (including apples, oranges, and grapes) also made the list. Processed agricultural goods such as

cocoa paste, cocoa butter, and frozen fish may reflect the availability of local raw materials.

The second panel of Table 3.3 reveals the quite different nature of the top 20 exports that were traded

within SSA, with a disproportionately high share of processed goods, including such items as cigarettes and

tobacco, frozen fish, sugar, palm oil, beer, soup, flour, milk and cream, and mineral water. In value terms,

nearly two-thirds of the agricultural products traded within SSA in 2013 were processed agricultural products.

Given the diversity of African countries, looking at SSA exports in total may well miss important

details. Are, for instance, exports of horticultural products from just a few countries? Appendix Table A.1

shows the composition of the top 20 agricultural exports for our 10 focus countries. The importance of

coffee, cocoa, and tea stands out at the country level: coffee (090111) was the most important agricultural

export item for Ethiopia, Rwanda, and Uganda, and was second and third in rank for Tanzania and Kenya,

respectively; cocoa beans (180100) were the leading export for Ghana and Nigeria in 2013, while black

tea (090240) was the most and second most important item for Kenya and Rwanda, respectively.

Horticultural products appear to be important for a number of our focus countries. For instance,

“other” vegetables (070990) and fresh cut flowers (060310) were the second and third most important

agricultural export goods for Ethiopia; fresh cut flowers (060310) were second most important for Kenya; and

fresh fruit such as oranges (080510), apples (080810), and grapes (080610) were the second, fourth, and fifth

ranked items for South Africa. Cashew nuts (080131) were the most important export item for Tanzania and

the second and fourth most important item for Ghana and Nigeria, respectively. A variety of processed food

items appears in the list including fish fillets, sugar, flour, vegetable oil, cigarettes, and alcoholic beverages.

16

Table 3.3 Composition of SSA’s top 20 exports to the world and to SSA, 2013

To the world To SSA

Rank HS6 Name Cat.* Share (%) Rank HS6 Name Cat.* Share (%)

1 180100 Cocoa beans, whole or broken B 12.8 1 240120 Unmanufactured tobacco B 7.9

2 090111 Coffee, not roasted, not decaffeinated B 4.7

2 240220 Cigarettes containing tobacco P 4.2

3 240120 Unmanufactured tobacco B 4.7

3 070990 Other vegetables, fresh or chilled H 3.9

4 120740 Sesamum seeds B 4.4

4 100590 Other maize (corn) B 3.2

5 090240 Black tea (fermented) and others B 3.8

5 030379 Frozen fish, excluding fish fillets P 2.9

6 060310 Fresh cut flowers H 2.7

6 170199 Other cane or beet sugar P 2.8

7 080131 Cashew nuts in shell H 2.7

7 170111 Raw sugar P 2.6

8 100590 Other maize (corn) B 2.2

8 151190 Other palm oil and its fractions P 2.4

9 170111 Raw sugar not containing added flavor P 2.1

9 220300 Beer made from malt P 2.3

10 180310 Cocoa paste, not defatted P 1.7

10 090240 Black tea (fermented) and others B 1.9

11 030379 Frozen fish, excluding fish fillets P 1.7

11 210410 Soups and broths and preparations P 1.8

12 170199 Other cane or beet sugar P 1.6

12 110100 Wheat or meslin flour P 1.8

13 070990 Other vegetables, fresh or chilled H 1.6

13 010290 Other live bovine animals B 1.7

14 240220 Cigarettes containing tobacco P 1.5

14 210690 Other food preparations P 1.4

15 180400 Cocoa butter, fat and oil P 1.5

15 080810 Apples H 1.3

16 080510 Oranges H 1.5

16 240110 Tobacco, not stemmed or stripped B 1.2

17 220421 Other wine; grape must with ferment P 1.3

17 240310 Smoking tobacco P 1.1

18 080610 Grapes H 1.2

18 230990 Other preparations for animal feeding P 1.1

19 080810 Apples H 1.1

19 040229 Powdered milk or cream P 1.0

20 160414 Fish, whole or in pieces P 1.1

20 220210 Waters, including mineral waters P 1.0

Source: Merchandise export data from Comtrade, accessed through World Integrated Trade Solution (World Bank 2016a).

Note: HS = Harmonized System. * B, H, and P represent bulk, horticulture, and processed agriculture, respectively.

17

The big hits change from one period to the next (Easterly and Reshef 2010) and a question arises

as to whether changes in the importance of agricultural exports are driven by new products. To answer the

question, we follow Kehoe and Ruhl (2013) in constructing the set of least-exported agricultural goods

which were originally either not exported or exported only in small quantities. Specifically, starting with

the smallest amounts of exports including zero, we add products to the set until the sum of their export

values reaches 2 percent of total export value in the initial period (“bottom 2 percent” items). To reduce

the chance that a good is typically exported but not exported in any one year (Kehoe and Ruhl 2013) and

to mitigate potential inaccuracy of the data reporting in the earlier years, we average each country’s

exports for the three earliest years for which the data are available in the Comtrade system.

Appendix Table A.2 reports the set of items that were bottom 2 percent in the earliest available

years, but made the top 20 list in 2013 for our focus countries. Except for Rwanda, the item that appeared

first in each list was either a horticultural or a processed agricultural product. For instance, while “other”

vegetables (070990) and fresh cut flowers (060310) were among the bottom 2 percent items at the turn of

the millennium in Ethiopia, they became the country’s second and third largest export goods in 2013.

Similarly, while bananas (080300) and almonds (080212) were among the bottom 2 percent goods for

Mozambique, they became Mozambique’s fifth and ninth most important agricultural exports in 2013.

The leading emerging processed goods include such products as palm kernel or babassu oil (151329) in

Ghana, cigarettes (240220) and cocoa paste (180310) in Nigeria, oil cake (230630) in Tanzania, and sugar

(170199) in Uganda. The emerging bulk products include oil seeds such as soya beans (120100) in

Ethiopia, sesamum seeds (120740) in Ghana, and other oil seeds (120799) in Tanzania and Nigeria,

perhaps reflecting rising demand for vegetable oils and animal feeds. For South Africa, in contrast, none

of the top 20 agricultural export items in 2013 came from the bottom 2 percent in earlier years.

One potential explanation for the low share of processed agricultural exports in Africa’s exports

on average is the relatively low income of most African countries. We know that a key feature of

consumer demand for food is that as incomes rise consumers shift from purchasing raw agricultural

products to products that embody more and more value-added services. To see whether Africa is

18

following that trend, or a distinctly different trend, we look at the relationship between real GDP and the

ratio of value-added in agricultural processing to value-added in agriculture, a relationship examined by

de Janvry (2009). Figure 3.3 reveals something close to a linear relationship between the ratio of value-

added in agricultural processing to value-added in agriculture. The African countries in the graph appear

broadly to follow this pattern. A dummy variable for Africa included in this regression failed to reveal a

significant difference between African and other countries. This suggests that the relatively low share of

agricultural processing in African economies reflects their relatively low incomes, rather than a specific

feature of African agriculture, such as the mix of commodities or consumer preferences.

Figure 3.3 The share of processed agricultural value added in total agricultural value added rises

with per capita income, 2011

Source: Global Trade Analysis Project Database, version 9. Horizontal axis shows GDP per capita in 2011.

Turning to the relationship between processed agricultural exports as a share of total agricultural

exports, we also find a positive relationship with real GDP, as Figure 3.4 shows. In this case, the

relationship appears to be nonlinear, with the rate of increase declining as incomes rise. However, there is

Pro

cesse

dS

hare

(%)

19

no indication either in the plot or from statistical testing that African countries are not following a similar

path to other countries.

Figure 3.4 The share of processed agricultural exports in total agricultural exports also rises with

per capita income, 2011

Source: Global Trade Analysis Project Database, version 9. Horizontal axis shows GDP per capita in 2011.

Pro

cesse

dS

hare

(%)

20

4. TRADE AND PROTECTION PATTERNS

In this section, we use the Global Trade Analysis Project (GTAP) Database to allow us to capture both

trade and protection, and to prepare for the simulation analysis undertaken in the next section. Using

this database, we find SSA’s agricultural exports were $46.0 billion in 2011 of which $21.8 billion

(47.4 percent), $7.4 billion (16.2 percent), and $16.8 billion (36.5 percent) were bulk, horticulture, and

processed agriculture, respectively (GTAP 9 Database).4 In doing this, we build on the insight from

Jensen, Robinson, and Tarp (2010) that the impact of a trade regime on production incentives requires a

general equilibrium treatment, going beyond the impacts captured in either the nominal or the effective

rate of protection.

Figure 4.1 shows the destinations of SSA’s exports for total, bulk, horticulture, and processed

agriculture. This shows that the European Union (EU) was the largest destination for SSA’s exports,

taking 39.6 percent of SSA’s exports (37.3 percent, 42.4 percent, and 41.3 percent of bulk, horticulture,

and processed agriculture, respectively). Nineteen percent of SSA’s exports went to SSA, with processed

agriculture to SSA disproportionately accounting for 34.9 percent of SSA’s total processed agriculture

exports. The EU and SSA combined accounted for about three-quarters of SSA’s processed agriculture

exports, while its exports of bulk agriculture were more geographically dispersed. The South Asia region

absorbed 17.7 percent of SSA’s horticultural exports.

4 “Bulk” includes paddy rice (pdr), wheat (wht), cereal grains nec (gro), oil seeds (osd), sugar cane, sugar beet (c_b), plant-

based fibers (pfb), crops nec (ocr), cattle, sheep, goats, horses (ctl), animal products nec (oap), raw milk (rmk), wool, silk-worm

cocoons (wol), and fishing (fsh). Vegetables, fruits, and nuts (v_f) is used as a proxy of “horticulture.” “Processed agriculture”

includes meat–cattle, sheep, goat, and horse (cmt), meat products nec (omt), vegetable oils and fats (vol), dairy products (mil),

processed rice (pcr), sugar (sgr), food products nec (ofd), and beverages and tobacco products (b_t). See the GTAP website for a

detailed product breakdown: www.gtap.agecon.purdue.edu/databases/contribute/detailedsector.asp.

21

Figure 4.1 Destinations of SSA’s exports, 2011

Source: Global Trade Analysis Project Database, version 9.

Note: ECA = Europe and Central Asia; EU = European Union; Kor/Taiwan/HK = Korea/Taiwan (China)/Hong Kong (China); LAC = Latin America and the Caribbean;

MENA = Middle East and North Africa; NZ = New Zealand; SA = South Asia; SEA = Southeast Asia; SSA = Sub-Saharan Africa.

SSA19%

ECA5%

EU40%

USA6%

Australia/NZ1%

Japan2%

China5%

Kor/Taiwan/HK2%

SEA5%

SA5%

LAC1%

MENA7%

Others2%

Total Agriculture

SSA9%

ECA6%

EU37%

USA8%

Australia/NZ0%

Japan2%

China9%

Kor/Taiwan/HK3%

SEA8%

SA4%

LAC1%

MENA10%

Others3%

Bulk

SSA12%

ECA5%

EU42%

USA3%

Australia/NZ0%

Japan1%

China1%

Kor/Taiwan/HK2%

SEA6%

SA18%

LAC1%

MENA7%

Others2%Horticulture

SSA35%

ECA3%

EU41%

USA5%

Australia/NZ1%

Japan3%

China1%

Kor/Taiwan/HK2%

SEA2%

SA1%

LAC1%

MENA4%

Others1%

Processed Ag

22

Columns 1 through 3 of Table 4.1 show the ad valorem equivalent (AVE) protection (Guimbard et

al. 2012) that SSA’s exports face, the AVE that SSA imposes against its imports, and the world AVE for

the purpose of comparison. The last four rows show the summary of AVE for agricultural goods. SSA’s

agricultural exports face an AVE of 7.0 percent in its export market (7.7 percent, 3.8 percent, 7.6 percent

for its bulk, horticulture, and processed agriculture exports, respectively), which is slightly lower than the

world average of 8.2 percent (8.3 percent, 5.2 percent, and 8.6 percent for bulk, horticulture, and processed

agriculture, respectively), perhaps reflecting its preferential access to certain developed countries including

the EU and the United States. The SSA’s own AVE against its agricultural imports of 12.2 percent was

about 50 percent higher than the world average.

Table 4.1 Structure of ad valorem equivalent protection

AVE in SSA’s exports and

imports and world average AVE in EU

AVE

SSA

SSA’s

exports

(%)

SSA’s

imports

(%)

World

average

(%)

Against

SSA

(%)

Against

others

(%)

EU

average

(%)

Intra-

SSA

(%)

1 pdr Paddy rice 1.2 3.5 7.1

0.9 3.8 2.7 1.8

2 wht Wheat 1.3 6.6 7.0

0.0 11.7 2.5 0.8

3 gro Cereal grains nec 71.2 3.4 26.0

0.0 2.6 0.6 2.8

4 v_f Vegetables, fruit, nuts 3.8 10.6 5.2

1.4 4.3 1.6 8.8

5 osd Oil seeds 7.0 4.6 8.3

0.0 0.0 0.0 2.5

6 c_b Sugar cane, sugar beet 0.4 0.2 0.5

1.0 1.5 0.8 0.0

7 pfb Plant-based fibers 1.7 1.9 2.2

0.0 0.0 0.0 1.5

8 ocr Crops nec 3.4 12.5 4.5

0.0 1.2 0.5 4.9

9 ctl Cattle, sheep, goats, horses 1.3 1.7 4.6

0.0 2.1 0.2 1.3

10 oap Animal products nec 2.6 7.7 3.3

0.0 2.5 0.6 5.3

11 rmk Raw milk 0.0 0.0 0.0

0.0 0.0 0.0 0.0

12 wol Wool, silk-worm cocoons 16.7 0.0 21.1

0.0 0.0 0.0 1.2

13 fsh Fishing 3.7 10.3 2.7

1.8 2.7 1.0 9.8

14 cmt Meat: cattle, sheep, goats, etc. 33.7 12.6 13.9

1.9 54.0 11.7 7.8

15 omt Meat products nec 5.0 12.3 13.0

2.5 19.1 2.1 5.9

16 vol Vegetable oils and fats 8.0 12.5 9.3

0.0 2.3 1.1 10.1

17 mil Dairy products 10.9 10.3 7.9

2.0 23.9 1.1 10.9

18 pcr Processed rice 5.7 9.9 16.6

0.8 15.8 7.2 7.4

19 sgr Sugar 9.1 15.6 12.5

1.2 43.8 12.3 23.4

20 ofd Food products nec 4.8 14.8 6.0

0.9 7.3 1.8 11.0

21 b_t Beverages, tobacco products 13.4 16.9 8.7

4.3 6.7 1.0 15.9

22 Others Nonagriculture 1.1 8.0 2.3

0.0 1.4 0.6 5.2

Total

1.7 8.7 2.9

0.1 1.8 0.7 6.1

23

Table 4.1 (continued)

Summary of agricultural AVE protection

SSA’s

exports

(%)

SSA’s

imports

(%)

World

average

(%)

Against

SSA

(%)

Against

others

(%)

EU

average

(%)

Intra-

SSA

(%)

Bulk 7.7 7.4 8.3 0.1 1.8 0.7 3.3

Horticulture 3.8 10.6 5.2 1.4 4.3 1.6 8.8

Processed agriculture 7.6 13.6 8.6 1.3 11.1 2.4 12.6

Total agriculture 7.0 12.2 8.2 0.8 7.3 2.0 10.1

Source: Global Trade Analysis Project Database, version 9.

Note: AVE = ad valorem equivalent; SSA = Sub-Saharan Africa; nec = not elsewhere classified; EU = European Union.

Columns 4 through 6 of Table 4.1 show the AVE that SSA faces in the EU market, the AVE that

the EU imposes against its imports other than from SSA and the EU, and the EU’s average AVE,

respectively. SSA enjoys preferential access to the EU market. Its preferential rate for agriculture of 0.8

percent on average is substantially lower than the rate the EU imposes against its suppliers other than SSA

and the EU itself (7.3 percent). In particular, SSA appears to benefit from the lower preferential rates for its

processed agricultural goods (1.3 percent on average) relative to the AVE the EU imposes against other

suppliers (11.1 percent on average). The preference margins appear to be especially large for such products

as meat (1.9 percent versus 54.0 percent), dairy products (2.0 percent versus 23.9 percent), and sugar (1.2

percent versus 43.8 percent).

In its export markets, SSA faces tariff escalation within many value chains: paddy rice (1.2 percent)

versus processed rice (5.7 percent); oil seeds (7.0 percent) versus vegetable oils and fats (8.0 percent); sugar

cane and sugar beet (0.4 percent) versus sugar (9.1 percent); raw milk (0.0 percent) versus dairy products

(10.9 percent); and cattle, sheep, goats, and horses (1.3 percent) versus animal products not elsewhere

classified (2.6 percent), cattle, sheep, goat, and horse meat (33.7 percent), and other meat products

(5.0 percent) (column 1 of Table 4.1). SSA’s own AVE against its imports (column 2), intra-SSA AVE (last

column), and world AVE (third column) also demonstrate similar tariff escalation.

In 2011, about one-fifth of SSA’s agricultural exports took place within SSA. Figure 4.2 visualizes

intra-SSA trade for agricultural goods. The horizontal and vertical axes represent exporting and importing

countries, respectively. The southwest corner represents the trade within the Economic Community of West

24

African States (ECOWAS); the northeast corner represents trade for the Southern African Development

Community (SADC); and the countries belonging to the Common Market for Eastern and Southern Africa

(COMESA) tend to be in between. Several countries are members of both COMESA and SADC. We

observe that the agricultural trade in SSA tends to occur in the same regions. The ECOWAS and the

COMESA/SADC countries rarely trade with each other for their agricultural goods (except for South

Africa, which exports agricultural goods to some ECOWAS countries). The last column of Table 4.1

reports the AVE for intra-SSA trade. Despite the presence of a number of trade blocs within Africa, AVE

protection for agricultural goods within SSA remains relatively high at 10.1 percent (higher than the world

average AVE of 8.2 percent), with an especially high AVE for processed agriculture, at 12.6 percent.

25

Figure 4.2 Intra-SSA direction of trade for agricultural goods, 2011 ($ million)

Source: Global Trade Analysis Project Database, version 9.

Note: The horizontal and vertical axes represent exporting and importing countries, respectively. The numbers along the vertical axis correspond to those along the horizontal axis.

1

3

5

7

9

11

13

15

17

19

21

23

0

100

200

300

400

500

600

700

26

5. SIMULATION SCENARIOS AND RESULTS: TRADE EFFECTS

In this section, we use the standard GTAP model (Hertel 1997), with the patterns of trade and protection

discussed in the previous section, to analyze the comparative-static impacts of different potential policy

reforms. By simulating the removal of protection, these experiments are intended to assess the effects of

the existing distortions on SSA’s agricultural trade rather than to evaluate specific impacts of any actual

trade reforms.

As this paper focuses on agro-processing and horticultural exports, the purpose of the simulations

is to measure trade effects.5 Simulation 1 considers the effects of removing tariff escalation in SSA

partner countries. Simulation 2 focuses on the loss of preferences in the EU. Simulation 3 considers

agricultural trade reform within major trading blocs in Africa. Simulation 4 considers the impact of higher

productivity in agricultural processing in Africa. Finally, Simulation 5 considers the impacts of SSA

countries removing all AVE protection, including protection of manufacturing and resources goods,

against all its trading partners.

Column 1 of Table 5.1 shows the simulation result from eliminating tariff escalation by SSA’s

partner countries, reducing their AVE protection for processed goods to the levels of unprocessed goods

in the same value chain identified above (for example, lowering the AVE rate of processed rice to the

level of paddy rice) (Simulation 1). SSA’s exports of processed goods increase by 114.3 percent while its

bulk and horticulture exports decrease slightly by 4.6 percent and 3.5 percent, respectively. Overall,

SSA’s agricultural exports would increase by 39.0 percent.6 These results show that tariff escalation in

external markets poses substantial barriers for SSA’s exports of processed agricultural products. While

SSA receives duty-free access from some partners such as the EU (and it is likely that the preferential

5 Since the model assumes full employment, further studies are required to assess employment effects. 6 The 5,056.8 percent increase in the exports of cattle, sheep, goat, and horse meat (cmt) appears to reflect initially very high

AVE protection imposed by some partner countries (for example, Norway) against SSA’s exports of this category. One caveat

on this exercise is that the AVE protection used in this paper does not include sanitary and phyto-sanitary (SPS) requirements

and that SPS issues frequently need to be addressed for new exports to take place. For instance, focusing on the case of foot-

and-mouth disease (FMD) in southern African countries, Scoones et al. (2010) report that the presence of FMD is a major obstacle

for these economies to gain access to international markets.

27

access creates incentives for processing in SSA), there appears to remain scope to increase agro-

processing exports further resulting from the removal of tariff escalation by other trading partners. The

dramatic increase in exports of processed agriculture from SSA under Simulation 1 suggests that the

provisions in the Doha Agenda proposals on reducing tariff escalation (WTO 2008, 18) may have very

favorable effects on exports of processed agricultural products from Africa. They make a case for policy

makers focusing on this issue in future trade negotiations.

Table 5.1 Simulation results: trade effects (%)

Sim 1 Sim 2 Sim 3 Sim 4 Sim 5

To Wld To EU To Wld

Intra-

SSA To Wld To Wld To Wld

1 pdr Paddy rice -9.87

-22.14 -2.96

9.01 -5.76 -5.76 9.05

2 wht Wheat -7.46

-61.76 -3.08

3.87 -3.24 -3.24 .-16.05

3 gro Cereal grains nec -1.54

-5.70 -0.44

2.95 -0.59 -0.59 1.76

4 v_f Vegetables, fruit, nuts -3.46

-8.58 -3.30

17.42 -1.89 -1.89 4.32

5 osd Oil seeds -5.63

1.31 1.09

6.36 -3.21 -3.21 5.16

6 c_b Sugar cane, sugar beet -7.21

1.30 1.96

1.42 -4.40 -4.40 8.80

7 pfb Plant-based fibers -3.83

0.48 0.67

4.42 -1.92 -1.92 6.21

8 ocr Crops nec -5.69

-4.92 -1.73

14.10 -3.03 -3.03 7.06

9 ctl Cattle, sheep, goats, horses 3.00

-7.04 0.20

2.36 -1.10 -1.10 2.60

10 oap Animal products nec 2.78

-5.92 -1.08

10.74 0.93 0.93 3.24

11 rmk Raw milk -10.48

1.94 1.61

0.00 0.81 0.81 13.71

12 wol Wool, silk-worm cocoons -9.48

1.92 1.96

2.02 -0.33 -0.33 26.47

13 fsh Fishing -2.80

-1.45 -0.65

16.24 -1.08 -1.08 4.09

14 cmt Meat: cattle, sheep, goat,

horse

5,056.80

-95.74 -28.99

48.44 77.81 77.81 8.88

15 omt Meat products nec 34.23

-72.99 -12.08

67.06 80.20 80.20 3.02

16 vol Vegetable oils and fats 35.31

-13.27 -1.90

52.56 50.95 50.95 10.16

17 mil Dairy products 194.54

-75.59 -6.03

90.31 45.98 45.98 36.78

18 pcr Processed rice 22.76

-50.50 -4.88

38.38 34.96 34.96 3.25

19 sgr Sugar 60.62

-83.72 -52.15

54.57 37.01 37.01 29.03

20 ofd Food products nec -1.82

-21.19 -9.77

29.66 28.63 28.63 7.71

21 b_t Beverages and tobacco

products

-0.49

-4.93 -1.48

20.33 7.87 7.87 7.94

22 Others Nonagriculture -2.96

0.41 0.38

-0.18 -1.36 -1.36 9.45

Total

1.10

-2.05 -0.19

4.91 -0.30 -0.30 9.27

28

Table 5.1 (continued)

Summary of agricultural exports changes (%)

To Wld To EU To Wld

Intra-

SSA To Wld To Wld To Wld

Bulk -4.58

-4.60 -1.04

8.24 0.28 -2.48 6.36

Horticulture -3.46

-8.58 -3.30

17.42 1.48 -1.89 4.32

Processed agriculture 114.27

-29.86 -12.20

37.57 13.08 30.31 10.50

Total agricultural exports 38.96

-14.91 -5.48

28.81 5.14 9.58 7.54

Source: Authors’ simulation results.

Note: Wld = world; EU = European Union; SSA =Sub-Saharan Africa; nec = not elsewhere classified.

Simulation 2 explores what happens if the SSA loses its preferential access to the EU market for

its agricultural goods, with the EU increasing AVE protection against SSA from the preferential rates to

those that the EU imposes against other suppliers (columns 2 and 3 of Table 5.1). SSA’s agricultural exports

to the EU would decrease by 14.9 percent, which would lead to a reduction of its overall agricultural exports

by 5.5 percent. As the EU’s AVE protection for processed agriculture against nonpreferential suppliers is

especially high, the loss of preferences would result in a sharp reduction in SSA’s exports of processed

agricultural products—by 29.9 percent to the EU, and by 12.2 percent to the world.

Simulation 3 investigates the impacts of ECOWAS, COMESA, and SADC countries reducing

their AVE agricultural protection against each other to zero within their regional arrangements (columns 4

and 5). The simulation is partly motivated by the potential for regional agricultural trade to contribute to

food security by enhancing the resilience of Africa’s food supply system (Badiane, Makombe, and

Bahiigwa 2013). The result shows that the agricultural liberalization within these trade blocs combined

would lead to the expansion of intra-SSA agricultural trade by 28.8 percent, while SSA’s total agricultural

exports to the world would increase by 5.1 percent. The results of this simulation reflect the effects of

removing agricultural barriers in general, and the tariff escalation within such barriers, and hence result in

more rapid growth in exports of processed agricultural products than in total agricultural exports

(37.6 percent and 13.1 percent increase in processed agricultural exports to SSA and to the world,

respectively). They illustrate the extent to which protection within Africa discourages export of all

agricultural items.

29

Simulation 4 explores what would happen if SSA countries were to increase total factor

productivity in processing of agricultural goods by 10 percent (sixth column of Table 5.1). This

simulation ignores the costs of bringing about such productivity gains and is intended to help identify the

areas in which the gains are likely largest and hence to identify priority areas for reform. The results

reveal that SSA’s exports of processed agriculture would expand by 30.3 percent; its exports of bulk and

horticulture goods would decrease slightly by 2.5 percent and by 1.9 percent respectively as some goods

are processed before being exported after transformation; and its overall agricultural exports would

expand by 9.6 percent. This simulation result is consistent with the literature on high productivity

associated with exports and highlights the importance of improving the productivity of agricultural

processing activities for expansion of these exports. This simulation understates the long-run impacts of

raising productivity in these sectors because the modeling framework that we use looks only at static

gains and does not allow for the emergence of new activities. Thus, it misses the extensive-margin impact

of increases in productivity, where higher productivity may cause new export activities to take place.

Simulation 5 involves complete removal of AVE protection against SSA’s imports including

nonagricultural goods. Perhaps not surprisingly, it leads to a much larger increase in total exports than any

of the other simulations (last column in Table 5.1). Because processing agricultural products is typically a

low-margin activity, we had anticipated that it might also result in a large increase in the share of

agricultural exports shipped in processed form. Three effects on processing exports from removing all

import protection can be anticipated: (1) the removal of each country’s own tariff escalation is likely to

reduce production of processed goods for domestic markets; (2) the removal of tariff escalation by

African partners increases opportunities for processing; and (3) reductions in the costs of inputs used in

processing would be expected to expand processing for both domestic and export markets. The model’s

results point to an increase in processed agricultural exports relative to bulk and horticultural exports,

suggesting that the reduction in production costs and the increase in market access opportunities would

30

outweigh the reduction in incentives to process for domestic markets. However, the increase in

agricultural exports is not much larger than the increase in overall exports.

31

6. POLICY QUESTIONS

The decision on whether to export a raw agricultural product should still be based solely on the

economics of the value-adding process. If, for instance, coffee may be exported in fresh or roasted form,

the decision on whether to undertake the roasting stage should depend only on the costs and returns

associated with undertaking that stage. The “great unbundling” (Baldwin 2006) means, however, that

other countries may well have become competitors for the bean-producing country in roasting the coffee.

Naïve calculations that consider only the value of the roasted beans relative to the value of the raw

beans—without considering the costs of the processing phase—are insufficient as a basis for deciding

whether to undertake the processing phase in the producing country.

In general, it seems sensible for policy makers to delegate to producing and processing firms the

decisions about whether to undertake particular stages of production, and to focus on providing an

enabling environment in which producers may be able to take advantage of those opportunities that

generate positive value-added. Only producing firms are likely to have the information needed to assess

whether it will pay them to undertake additional processing. However, in the unbundled trade system, it is

now much more important for governments to keep channels of communication open to identify when

specific constraints that might be relaxed are preventing the emergence of particular processing stages in

the country. If there are, for example, high tariffs on inputs needed in the production process, this may

turn out to make it uneconomic to process the good domestically even though doing so would add value

at world prices. Another important source of elevated costs is weaknesses in infrastructure, such as

transport, electricity and water, or excessive costs of customs clearance, that may make otherwise high-

return activities privately unprofitable. A key step for governments is to identify where they can reduce

some of these costs to enable firms to undertake processing operations that would be economically

worthwhile?

Vulnerability to excess costs is particularly acute for processing activities because those activities

frequently operate on small margins relative to, say, production of a traditional export. Traditional exports

32

such as coffee frequently embody an especially large share of rents that can be dissipated—particularly in

the short term—without the activity shutting down. Consider, for example, the decision on whether to

export live cattle or chilled, boxed, deboned beef. The livestock herder is likely to be cash poor and

willing to sell cattle even if the price is quite far below the expected level and to be little affected by

distortions in input markets. By contrast, the returns from slaughtering, boning, and packing beef are

likely to be quite small relative to the cost of the animal and the needed intermediate inputs. If, for

example, the beef from a $100 animal is valued at $150 on the world market and intermediate inputs and

labor costs account for $35 of the $50 difference, increases in the cost of intermediate inputs or labor

could easily wipe out the needed returns from processing and either block the emergence of this activity

or cause it to shut down.

If we find that high tariffs and other charges on intermediate inputs result in negative value-added

(at market prices) in at least some processing activities, the disincentive to undertaking these activities

may result in economically desirable processing not being undertaken. If the government wishes, it may

deal with these problems either by reforming its tariffs and customs regimes or by specific export-focused

policy responses such as providing duty exemptions on intermediates used in the production of exports.

Responses of this type would not require negotiations with trading partners.

Another potential cause of failure to undertake desirable processing actions arises from

distortions imposed by trading partners. A key challenge for processing in developing countries comes

from tariff escalation in importing markets. In this situation, the tariff in the importing market is low on

raw materials, higher on intermediates, and highest on final consumer goods. This policy option creates—

and typically is intended to create—incentives to undertake processing in the importing country and to

discourage processing in the exporting country. Such incentives could be countered by the exporting

country, but this action would surely be difficult to undertake successfully. However, information on the

extent of such tariff escalation is likely to be useful background for tariff negotiations.

33

The impact of tariff escalation is likely to be turned on its head when considering exporters that

have access to effective preferences for raw and processed products. If we assume that processing a good

adds 20 percent to its initial value, then a tariff margin of 20 percent between the raw and the processed

form of a product creates a 100 percent effective rate of protection on the processing activity. Under a

nondiscriminatory tariff regime, this assistance is provided to processors in the importing country. If this

tariff applies against imports of most producers but some small producers receive a tariff preference, the

20 percent effective rate of protection may be available to processors in the exporting market.

Comparison of the mix of processing in preference- and non-preference-receiving exporters may provide

some indication of the effectiveness of the preference regime in creating incentives for additional

processing in exporting countries.

Developing new exports from Africa is both vitally important and very challenging. Some of the

barriers that have been identified—such as geography and landlocked status (Freund and Rocha 2011)—

are inherent, but their effects can be addressed by adequate policy reforms and associated investments.

For instance, in examining the effect of trade times on Africa’s exports of new products, Freund and

Rocha (2011) report that reducing inland transit times significantly boosts exports (especially for time-

sensitive agricultural exports) and suggest the importance of investments on inland transportation and

infrastructure. Bouët, Cosnard, and Laborde (2017, fig. 2.4) show that the costs associated with time for

border and documentary compliance are high especially for agricultural products for many African

countries.

The stylized fact emerging from the recent literature on exporting firms that a small number of

highly productive firms generally dominate exporting activities (Bernard et al. 2007) would seem to allay

the concerns expressed by Hausmann and Rodrik (2003) that firms investing in costly discovery of

successful exports lose the returns from export success through entry of copycat firms. In this situation, it

seems possible, and perhaps vital, to create a situation that stimulates firms to invest in discovery of new

opportunities. Approaches to creating incentives for innovative exports by providing protection to sales

34

on the domestic market appear to have little applicability in Africa. Large domestic markets for these

products only rarely exist, and even if they do, they are likely to become saturated relatively rapidly,

leaving innovators with low returns on their investment. While export subsidies for developing countries

are only loosely constrained by World Trade Organization (WTO) rules (Creskoff and Walkenhorst

2009)—and are almost unconstrained for least developed countries and countries whose per capita GDP is

under $1,000 in 1990 dollars—the fiscal costs of such export subsidies are likely to be very high. Fiscal

problems are likely to arise with the third policy option considered by Hausmann and Rodrik (2003,

630)—the provision of grants and subsidies to chosen firms. If such subsidies are large enough to make a

difference, they are likely to be very costly. Further, Farole (2011, 173) finds that such incentives are

associated with poorer performance in African economic zones.

In contrast, the approach of providing a relatively level playing field on which exporters can

experiment in order to identify successful exports seems promising. One approach to providing an

environment for experimentation is to allow exporters to access intermediate inputs for use in production

of exports at world prices. In China, duty exemptions were a central feature of its economic reforms,

allowing exporters to use imported materials and to increase processed exports in a wide range of labor-

intensive activities (Ianchovichina 2004). Other successful exporters of industrial goods—for instance,

Cambodia, Mauritius, Tunisia, and Vietnam—also established a “free trade regime for exporters” through

a variety of mechanisms such as tariff exemptions, duty drawbacks, and rebates of indirect taxes

(Newman et al. 2016a).

A duty exemption or duty drawback system reduces the burden imposed by a country’s own

protection regime and decreases the inefficiency associated with the country’s trade regime by

eliminating the negative effective rates of protection resulting from exporters having to pay import duties

on their intermediate inputs while receiving no protection on their outputs. Given the low margins

inherent in many processing activities, this problem of negative protection can frequently explain the

absence of many highly productive export activities. Duty exemptions, under which duties are waived on

35

imported inputs subject to subsequent verification of their incorporation in exports, are strongly preferred

by exporters to duty drawbacks where duties must be paid and are—in principle—refunded on export of

the final good. A related export facilitation mechanism needed in countries applying a value-added tax

(VAT) is a refund of the VAT paid on intermediate inputs used in the production of exports. This is an

inherent feature of any destination VAT and not a special export processing incentive. It, like a duty

exemption arrangement, is fully consistent with WTO rules on subsidies (Creskoff and Walkenhorst 2009).

Duty exemptions and VAT refund mechanisms are frequently part of more comprehensive export

promotion mechanisms such as special economic zones (SEZs) (Farole 2011). SEZs typically involve

other features, such as improved infrastructure, and a different regulatory environment from the rest of the

economy. Frequently, this environment is designed to attract foreign direct investment. Collier and Page

(2009) point to strong advantages if they are located in geographically favored regions near infrastructure.

Farole (2011, ch. 8) finds that African zones have encountered difficulties in a number of areas, including

unreliability of power supply relative to Asian zones, slow customs procedures, and wage rates that are

high relative to labor productivity.

The high wage rates relative to productivity seem surprising given the very low incomes

prevailing in much of SSA. This may reflect some sort of insider–outsider distinction that results in

relatively high wage rates for a relatively small volume of output and level of employment. Using

Farole’s (2011, table 8.2) numbers on output per person in the zones and adding 2014 GDP per person,

Table 6.1 shows that wage rates in the African SEZs are almost 90 percent of wage rates in his four

comparator countries, even though GDP per capita, and, hence, likely the opportunity cost of labor to the

zone, is only 42 percent of the level in the comparator countries. The difference is even more stark with

the two highly successful Asian comparators—Bangladesh and Vietnam—where wages average less than

half the African rate even though national incomes are higher.

36

Table 6.1 Output per worker and the cost of labor in special economic zones and

economy-wide GDP per capita

Output/worker

($ 2008)

Wage

($)

GDP/capita

($)

Bangladesh 11,715 46 1,087

Dominican Republic 45,063 225 6,164

Honduras 37,921 313 2,435

Vietnam 15,167 102 2,052

Average 27,467 172 2,934

Ghana 37,294 118 1,442

Kenya 13,646 117 1,358

Lesotho 9,913 150 1,034

Senegal 12,433 225 1,067

Average 18,322 153 1,225

Source: Authors’ calculations based on Farole (2011, table 8.2) and World Development Indicators for GDP/

capita for 2014 (World Bank 2016b). The wage column refers to the average monthly cost of unskilled workers.

Note: GDP = gross domestic product.

Following his detailed consideration of SEZs in Africa, Farole recommends that African policy

makers consider processing of agricultural and resource exports in addition to labor-intensive

manufactures that have been the focus of export processing activities in Asia. It seems to us that this may

be a part—but surely only a part—of the solution to the problem of stimulating a takeoff of new exports

from Africa.

Drawing on the lessons of recent decades, it seems more likely to us that deep, sustained growth

in exports from SSA will result from policies that provide as much scope as possible for entrepreneurs to

search and discover, in the sense suggested by Hausmann and Rodrik (2003), the products that will be the

highly successful exports of the future. Making sure that a wide range of potential exporters have access

to the intermediate inputs they need seems likely substantially to expand the range of products with which

potential exporters can experiment. Current, generally closed, SEZs do not seem to have worked very

well in doing this, despite the provision of duty exemptions on intermediates, improved infrastructure,

and fiscal incentives. Perhaps one way to overcome these challenges is to draw from China’s experience

and to extend the most important of these incentives—the duty exemptions for intermediates used in the

production of exports—to export processors of all kinds throughout each country. Once processors of

37

agricultural products, along with producers of other potential exports, have access to intermediates at

world prices and to labor and other inputs at domestic prices, their experimentation is likely to lead to

identification of exports that will become the future big hits and mainstays of higher levels of future

exports. As argued by Newman et al. (2016b), it is not enough just to improve the investment climate—

which nevertheless remains a high priority—but what is needed is a broader push for export development

of the type seen in countries such as Vietnam and Cambodia.

38

7. CONCLUSIONS

The recent focus on the potential for agricultural processing and horticultural exports as growth engines

for Africa appears to be driven in part by pessimism about the prospects for growth of manufacturing

exports of the type that have been so stunningly successful in driving export growth from many Asian

countries. Key questions include whether this pessimism is warranted, and whether the agricultural

processing and horticultural exports can become the engine of growth so much needed to promote African

development.

New developments in economics have given us new insights into the growth of exports that are

highly relevant for analysis of this question. We now know that exports of any country tend to be

dominated by a relatively small number of products, often exported to a relatively small number of

markets (Easterly and Reshef 2009, 2010), and frequently by a small number of highly productive firms.

This reduces the concerns that have been expressed by authors such as Hausmann and Rodrik (2003)

about the risk that innovators will not be able to recoup their fixed costs of discovery because of excessive

entry of imitators.

When we look at the pattern of exports from African countries, we find that the share of

agricultural exports has declined to around 10 percent of the total, somewhat less than the 12 percent of

exports accounted for by nonfactor services. This is a very small share on which to build if the goal is to

stimulate dramatic growth in exports through exports of horticultural or processed agricultural products.

Within agricultural exports, the share of traditional, bulk agricultural exports has fallen sharply, from 60

to 42 percent, although this is now twice the share of such exports in global trade. Where Africa does

stand out is in the share of horticultural products in total exports—more than 22 percent of agricultural

exports in 2014 as against 12 percent for the world as a whole.

The relatively low—but rising—share of processed agricultural exports from Africa may reflect

the relatively low incomes in African countries. When we plot the share of value-added of processed

agriculture relative to total agriculture in Africa against real incomes, we find no need for an Africa-

39

specific explanation. Most of the observations are distributed around a rising trend. When we look at the

share of exports, African exports of processed products relative to total agricultural exports also seem to

follow the same broad relationship as other countries, in this case a quadratic response to income growth.

Simulation analysis is used to examine the response of processed agricultural exports from Africa

to changes in protection rates and productivity growth in processing. The results suggest that tariff

escalation in export markets has powerful impacts. Cutting protection on processed agricultural products

in export markets would substantially increase exports of processed products from Africa. Cutting

agricultural protection within main African trade blocs and extending liberalization to all the trading

partners and to all the goods would similarly increase exports of processed agricultural products.

Our overall assessment is that increased exports of processed agricultural products could be a

worthwhile contributor to an overall upturn in African agricultural exports. Horticultural products could

also contribute to such a turnaround. However, our view is that policy makers should think much more

broadly, in a way that the export promotion strategy for these products is consistent with the development

of other export-oriented goods and services. As trading costs in Africa remain relatively high, including

import duties, transportation costs, documentary and border compliance costs, and other nontariff

measures (Bouët, Cosnard, and Laborde 2017), policy reforms and associated investments appear to be

necessary. For instance, one of the promising ways to encourage a surge in agro-processing and other

exports would be to reduce the cost of intermediate inputs generally. Reducing this disadvantage for

exports—ideally by reducing protection, but perhaps initially by ensuring that all exporters have access to

intermediates at world prices—is likely to stimulate growth in a wide range of exports as entrepreneurs

discover what exports best use the country’s skills and resources.

40

APPENDIX

Table A.1 Composition of top 20 agricultural exports at the country level, 2013 ($1,000)

Ethiopia Ghana

Rank HS6 Name Cat.* 2013

HS6 Name Cat.* 2013

1 090111 Coffee, not roasted B 770618

180100 Cocoa beans, raw or roasted B 1380501

2 070990 Other vegetables, fresh or chilled H 558771

080131 Cashew nuts in shell H 232581

3 060310 Fresh cut flowers H 527056

080132 Cashew nuts, shelled H 184282

4 120740 Sesamum seeds B 494808

151329 Palm kernel or babassu oil P 104550

5 010290 Other live bovine animals B 215168

180400 Cocoa butter, fat and oil P 65701

6 071333 Beans (Vigna spp., Phaseolus spp.) H 149442

120740 Sesamum seeds B 33448

7 010600 Other live animals B 73595

151110 Palm oil, whether or not refined P 31851

8 020450 Meat of goats P 63640

120810 Flours and meals of oil seeds or fruits P 24416

9 060210 Other live plants (including roots) H 62582

120799 Other oil seeds and oleaginous fruits B 20340

10 010410 Sheep B 47550

071490 Manioc, Jerusalem artichokes H 19710

11 071320 Dried leguminous vegetables P 40711

220890 Other ethyl alcohol P 18750

12 120799 Other oil seeds and oleaginous fruits B 31387

080290 Other nuts, fresh or dried H 16292

13 070190 Potatoes, fresh or chilled H 30916

151190 Other palm oil and its fractions P 15867

14 071350 Broad beans (Vicia faba var. major) H 24266

220850 Gin and geneva P 15085

15 120100 Soya beans, whether or not broken B 23463

190110 Malt extract P 14596

16 071390 Dried leguminous vegetables H 18605

151710 Margarine, excl. liquid margarine P 14435

17 091010 Ginger H 13554

151321 Palm kernel or babassu oil P 12674

18 130190 Lac; natural gums, resins H 12185

151590 Other fixed vegetable fats and oils P 11184

19 230640 Oil-cake and other solid residues P 10454

220720 Ethyl alcohol and other spirits P 11163

20 070200 Tomatoes, fresh or chilled H 9765

200811 Nuts, ground-nuts and other seeds H 7739

(continued)

41

Table A.1 (continued)

Kenya Mozambique

Rank HS6 Name Cat.* 2013

HS6 Name Cat.* 2013

1 090240 Black tea (fermented) and others B 1202919 240120 Unmanufactured tobacco B 249879

2 060310 Fresh cut flowers H 477890 170111 Raw sugar not containing added flav. B 185708

3 090111 Coffee, not roasted, not decaf B 189569 030613 Frozen shrimps and prawns P 31484

4 070820 Beans (Vigna spp., Phaseolus spp.) H 96782 120740 Sesamum seeds B 30178

5 240220 Cigarettes containing tobacco P 89062 080300 Bananas, including plantains, fresh H 22146

6 200820 Pineapples H 68866 080132 Cashew nuts, shelled H 16123

7 151190 Other palm oil and its fractions P 62259 120220 Ground-nuts, shelled H 13737

8 060210 Other live plants H 51900 230230 Bran, sharps and other residues P 10519

9 220300 Beer made from malt P 42656 080212 Almonds, shelled H 8648

10 140490 Vegetable products nes P 37738 151211 Sunflower-seed or safflower oil P 7449

11 170410 Chewing gum P 36018 240110 Tobacco, not stemmed/stripped B 7418

12 240120 Unmanufactured tobacco B 35993 080131 Cashew nuts in shell H 6370

13 200559 Beans (Vigna spp., Phaseolus spp.) H 34268 120720 Cotton seeds B 5761

14 080440 Avocados H 29283 151219 Sunflower-seed or safflower oil P 5651

15 170490 Other sugar confectionery P 26744 071390 Dried leguminous vegetables P 5452

16 151710 Margarine P 25983 090240 Black tea (fermented) and others B 4948

17 071333 Beans (Vigna spp., Phaseolus spp.) H 25415 170310 Cane molasses P 4761

18 200940 Pineapple juice P 21577 110100 Wheat or meslin flour P 4554

19 151620 Vegetable fats and oils P 21417 030559 Dried fish P 4325

20 240399 Other manufactured tobacco P 19361 071310 Peas (Pisum sativum) H 4244

(continued)

42

Table A.1 (continued)

Nigeria Rwanda

Rank HS6 Name Cat.* 2013

HS6 Name Cat.* 2013

1 180100 Cocoa beans, raw or roasted B 1542736

090111 Coffee, not roasted, not decaf B 49884

2 120740 Sesamum seeds B 842682

090240 Black tea (fermented) and others B 41906

3 180400 Cocoa butter, fat and oil P 269928

090230 Black tea (fermented) and partly ferm. B 19678

4 080131 Cashew nuts in shell H 238217

220300 Beer made from malt P 17770

5 100190 Other wheat and meslin B 194321

110100 Wheat or meslin flour P 13241

6 030613 Frozen shrimps and prawns P 169411

170199 Other cane or beet sugar P 9565

7 240220 Cigarettes containing tobacco P 163479

151620 Vegetable fats and oils P 7255

8 060390 Other cut flowers and flower buds H 153789

010290 Other live bovine animals B 7149

9 040229 Powdered milk or cream P 124572

100630 Semi-milled or wholly milled rice P 7067

10 180310 Cocoa paste, not defatted P 115512

110220 Maize (corn) flour P 6606

11 091010 Ginger H 94213

220290 Waters, including mineral waters P 6588

12 180200 Cocoa shells, husks, skins and other P 69742

100640 Broken rice B 5212

13 190220 Stuffed pasta, whether or not cooked P 55203

121190 Plants and parts of plants H 4052

14 040221 Powdered milk and cream P 55002

190530 Sweet biscuits; waffles and wafers P 3252

15 130120 Gum Arabic P 53994

090190 Coffee, whether or not roasted B 2305

16 030379 Frozen fish , excluding fish fillets P 46513

100590 Other maize (corn) B 2145

17 080132 Cashew nuts, shelled H 43051

110290 Cereal flours other than wheat P 1964

18 200819 Nuts, ground-nuts and other seeds H 42560

110311 Groats and meal of wheat P 1548

19 220210 Waters, including mineral waters an P 30942

070820 Beans (Vigna, Phaseolus spp.) H 1428

20 120799 Other oil seeds and oleaginous fruits B 24666

210320 Tomato ketchup and other tom sauce P 1244

(continued)

43

Table A.1 (continued)

South Africa Senegal

Rank HS6 Name Cat.* 2013

HS6 Name Cat.* 2013

1 100590 Other maize (corn) B 695949

210410 Soups and broths P 122797

2 080510 Oranges H 589592

030379 Frozen fish, excluding fish fillets P 111698

3 220421 Other wine P 507557

030269 Other fish, fresh or chilled B 56675

4 080810 Apples H 443291

240220 Cigarettes containing tobacco P 50724

5 080610 Grapes H 441039

240310 Smoking tobacco P 48286

6 220429 Other wine P 326723

190190 Malt extract; food prep of flour P 39449

7 170199 Other cane or beet sugar P 214754

040221 Milk and cream P 37365

8 170111 Raw sugar not containing added flav. B 208419

100640 Broken rice B 37037

9 240220 Cigarettes containing tobacco P 193597

150810 Ground-nut oil and its fractions P 36896

10 080820 Pears and quinces H 192010

240120 Unmanufactured tobacco B 26637

11 080290 Other nuts, fresh or dried H 186563

030613 Frozen shrimps and prawns P 25596

12 210690 Other food preparations P 162961

120220 Ground-nuts, shelled H 21421

13 080530 Lemons H 129522

030349 Tunas (of the genus Thunnus) P 17027

14 080520 Mandarins H 126510

070990 Other vegetables, fresh or chilled H 16775

15 080540 Grapefruit H 125337

070820 Beans (Vigna spp., Phaseolus spp.) H 15411

16 110313 Groats and meal of maize (corn) P 109430

030749 Cuttle fish B 13976

17 230990 Other reparations in animal feeding P 106517

080711 Melons (including watermelons) H 13905

18 030420 Frozen fillets P 98736

070200 Tomatoes, fresh or chilled H 13346

19 151219 Sunflower-seed or safflower oil P 96748

030759 Octopus B 12361

20 220710 Undenatured ethyl alcohol P 92489

160414 Fish, whole or in pieces P 9386

(continued)

44

Table A.1 (continued)

Tanzania Uganda

Rank HS6 Name Cat.* 2013

HS6 Name Cat.* 2013

1 080131 Cashew nuts in shell H 164905

090111 Coffee, not roasted, not decaf B 424457

2 090111 Coffee, not roasted not decaf B 160405

030410 Fish fillets and other fish meat P 95614

3 120740 Sesamum seeds B 124540

240120 Unmanufactured tobacco B 84114

4 240120 Unmanufactured tobacco B 91551

170199 Other cane or beet sugar P 67766

5 170199 Other cane or beet sugar P 69502

090240 Black tea (fermented) and others B 59013

6 071310 Peas (Pisum sativum) H 57097

180100 Cocoa beans, raw or roasted B 54833

7 090240 Black tea (fermented) and others B 54306

151620 Vegetable fats and oils P 47259

8 030490 Fish fillets and other fish meat P 46831

151190 Other palm oil and its fractions P 40342

9 090700 Cloves H 43061

240110 Tobacco, not stemmed/stripped B 30852

10 030420 Frozen fillets P 39578

110100 Wheat or meslin flour P 29745

11 110100 Wheat or meslin flour P 38740

060240 Roses, grafted or not H 28715

12 030410 Fish fillets and other fish meat P 27436

120740 Sesamum seeds B 28459

13 230630 Oil cake of sunflower seeds P 24942

060210 Other live plants (including roots) H 25750

14 170191 Cane or beet sugar P 24939

220300 Beer made from malt P 23698

15 240290 Cigars, cheroots, cigarillos, cigarettes P 23524

090230 Black tea (fermented) B 22871

16 080132 Cashew nuts, shelled H 23269

100640 Broken rice B 18850

17 180100 Cocoa beans, raw or roasted B 16361

100510 Maize (corn) seed B 18501

18 120799 Other oil seeds and oleaginous fruits B 15879

100630 Semi-milled or wholly milled rice P 17733

19 071390 Dried leguminous vegetables P 14517

030559 Dried fish, whether or not salted P 16646

20 060210 Other live plants H 14164

110220 Maize (corn) flour P 15387

Source: Merchandise export data from Comtrade, accessed through World Integrated Trade Solution (World Bank 2016a).

Note: HS = Harmonized System; nes = not elsewhere specified. * B, H, and P represent bulk, horticulture, and processed agriculture, respectively.

45

Table A.2 List of bottom 2 percent items that made top 20 list in 2013

Ethiopia

Average of 2001, 2002, 2003 2013

HS6 Name Cat.*

Exports

($1,000)

Share

(%) Rank

Exports

($1,000)

Share

(%) Rank

070990 Other vegetables, fresh or chilled H 0.5 0.000 220 558771 16.90 2

060310 Fresh cut flowers H 152.4 0.043 57 527056 15.94 3

010290 Other live bovine animals B 130.0 0.037 62 215168 6.51 5

010600 Other live animals B 131.7 0.037 61 73595 2.23 7

060210 Other live plants (including their roots) H 0.1 0.000 270 62582 1.89 9

010410 Sheep B 151.9 0.043 58 47550 1.44 10

120100 Soya beans, whether or not broken B 43.4 0.012 83 23463 0.71 15

071390 Dried leguminous vegetables P 110.1 0.031 70 18605 0.56 16

230640 Oil-cake and other solid residues P 0.0 0.000 10454 0.32 19

Ghana

Average of 2003, 2004, 2005 2013

HS6 Name Cat.*

Exports

($1,000)

Share

(%) Rank

Exports

($1,000)

Share

(%) Rank

151329 Palm kernel or babassu oil P 56.8 0.004 155 104550 4.47 4

120740 Sesamum seeds B 348.0 0.027 67 33448 1.43 6

120810 Flours and meals of oil seeds P 57.3 0.005 153 24416 1.04 8

220890 Other undenatured ethyl alcohol P 4.4 0.000 292 18750 0.80 11

080290 Other nuts, fresh or dried H 106.7 0.008 120 16292 0.70 12

220850 Gin and Geneva P 84.4 0.007 132 15085 0.64 14

151321 Palm kernel or babassu oil P 10.2 0.001 248 12674 0.54 17

220720 Ethyl alcohol and other spirits P 9.8 0.001 250 11163 0.48 19

(continued)

46

Table A.2 (continued)

Kenya

Average of 1997, 1998, 1999 2013

HS6 Name Cat.*

Exports

($1,000)

Share

(%) Rank

Exports

($1,000)

Share

(%) Rank

140490 Vegetable products not specified P 431.5 0.037 77 37738 1.24 10

071333 Beans (vigna spp., phaseolus spp.) H 88.5 0.008 137 25415 0.84 17

240399 Other manufactured tobacco P 495.8 0.042 70 19361 0.64 20

Mozambique

Average of 2001, 2002, 2003 2013

HS6 Name Cat.*

Exports

($1,000)

Share

(%) Rank

Exports

($1,000)

Share

(%) Rank

080300 Bananas, including plantains, fresh H 0.0

0.0 22146 3.29 5

080212 Almonds, shelled H 90.1 0.049 54 8648 1.28 9

151211 Sunflower-seed or safflower oil P 7.3 0.004 128 7449 1.11 10

151219 Sunflower-seed or safflower oil P 16.3 0.009 97 5651 0.84 14

071390 Dried leguminous vegetables P 31.0 0.017 77 5452 0.81 15

Nigeria

Average of 1999, 2000, 2001 2013

HS6 Name Cat.*

Exports

($1,000)

Share

(%) Rank

Exports

($1,000)

Share

(%) Rank

240220 Cigarettes containing tobacco P 0.7 0.0023 104 163479 3.41 7

060390 Other cut flowers and flower buds H 0.0 0.0000 153789 3.20 8

180310 Cocoa paste, not defatted P 0.0 0.0000 115512 2.41 10

180200 Cocoa shells, husks, skins and others B 0.0 0.0000 69742 1.45 12

190220 Stuffed pasta, whether or not cooked P 0.0 0.0000 55203 1.15 13

030379 Frozen fish, excluding fish fillets P 0.1 0.0002 155 46513 0.97 16

080132 Cashew nuts, shelled H 0.2 0.0007 131 43051 0.90 17

200819 Nuts, ground-nuts and other seeds H 0.0 0.0000 42560 0.89 18

220210 Waters, including mineral waters P 2.8 0.0089 77 30942 0.64 19

47

Table A.2 (continued)

Rwanda

Average of 2001, 2002, 2003 2013

HS6 Name Cat.*

Exports

($1,000)

Share

(%) Rank

Exports

($1,000)

Share

(%) Rank

120799 Other oil seeds and oleaginous fruits B 0.8 0.0025 102 24666 0.51 20

090240 Black tea (fermented) and others B 1.6 0.008 34 41906 18.56 2

090230 Black tea (fermented) and partly fermented B 0.0 0.000 398 19678 8.72 3

220300 Beer made from malt P 1.7 0.008 32 17770 7.87 4

110100 Wheat or meslin flour P 0.0 0.000 364 13241 5.87 5

170199 Other cane or beet sugar P 9.3 0.046 19 9565 4.24 6

151620 Vegetable fats and oils P 3.6 0.018 27 7255 3.21 7

010290 Other live bovine animals B 0.0 0.000 702 7149 3.17 8

100630 Semi-milled or wholly milled rice P 0.0 0.000 369 7067 3.13 9

110220 Maize (corn) flour P 0.0 0.000 362 6606 2.93 10

220290 Waters, including mineral waters P 72.4 0.359 8 6588 2.92 11

121190 Plants and parts of plants H 1.3 0.006 36 4052 1.79 13

190530 Sweet biscuits; waffles and wafers P 1.2 0.006 37 3252 1.44 14

090190 Coffee, whether or not roasted B 0.0 0.000 401 2305 1.02 15

100590 Other maize (corn) B 0.7 0.003 42 2145 0.95 16

110290 Cereal flours other than of wheat or meslin P 0.0 0.000 360 1964 0.87 17

110311 Groats and meal—of wheat P 0.0 0.000 359 1548 0.69 18

070820 Beans (vigna spp., phaseolus spp.) H 0.0 0.000 488 1428 0.63 19

210320 Tomato ketchup and other tomato sauce P 10.8 0.053 17 1244 0.55 20

Senegal

Average of 1996, 1997, 1998 2013

HS6 Name Cat.*

Exports

($1,000)

Share

(%) Rank

Exports

($1,000)

Share

(%) Rank

190190 Malt extract; food preparations of flour P 0.7 0.001 239 39449 4.46 6

030349 Tunas (of the genus thunnus) P 11.5 0.023 117 17027 1.93 13

080711 Melons (including watermelons) H 0.4 0.001 252 13905 1.57 17

(continued)

48

Table A.2 (continued)

Tanzania

Average of 1997, 1998, 1999 2013

HS6 Name Cat.*

Exports

($1,000)

Share

(%) Rank

Exports

($1,000)

Share

(%) Rank

230630 Oil cake of sunflower seeds P 170.4 0.040 70 24942 1.85 13

170191 Cane or beet sugar and sucrose P 0.0 0.000 509 24939 1.85 14

240290 Cigars, cheroots, cigarillos and cigarettes P 27.0 0.006 160 23524 1.75 15

120799 Other oil seeds and oleaginous fruits B 23.2 0.005 166 15879 1.18 18

071390 Dried leguminous vegetables P 50.7 0.012 117 14517 1.08 19

Uganda

Average of 1996, 1997, 1998 2013

HS6 Name Cat.*

Exports

($1,000)

Share

(%) Rank

Exports

($1,000)

Share

(%) Rank

170199 Other cane or beet sugar P 48.0 0.011 88 67766 4.85 4

060210 Other live plants (including their roots) H 155.0 0.037 60 25750 1.84 13

220300 Beer made from malt P 162.2 0.038 59 23698 1.70 14

100640 Broken rice B 170.9 0.040 57 18850 1.35 16

100510 Maize (corn) seed B 266.6 0.063 48 18501 1.33 17

100630 Semi-milled or wholly milled rice P 77.4 0.018 75 17733 1.27 18

Source: Merchandise export data from Comtrade, accessed through World Integrated Trade Solution (World Bank 2016a).

Note: HS = Harmonized System. * B, H, and P represent bulk, horticulture, and processed agriculture, respectively.

49

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